Bayes' rule : a tutorial introduction to Bayesian analysis /
Stone, James V., Dr,
Bayes' rule : a tutorial introduction to Bayesian analysis / James V Stone. - First Edition. - 170 pages : illustrations ; 23 cm
"A tutorial introduction book"--Page 4 of cover.
Includes bibliographical references and index.
An introduction to Bayes' rule -- Bayes' rule in pictures -- Discrete parameter values -- Continuous parameter values -- Gaussian parameter estimation -- A bird's eye view of Bayes' rule -- Bayesian wars -- Appendices. A. Glossary ; B. Mathematical symbols ; C. The rules of probability ; D. Probability density functions ; E. The binomial distribution ; F. The Gaussian distribution ; G. Least-squares estimation ; H. Reference priors ; I. MatLab code.
"Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. Bayes' rule is derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and online Python programs provided. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for the novice who wishes to become familiar with the basic principles of Bayesian analysis."--Publisher's description.
0956372848 9780956372840
Bayesian statistical decision theory.
QA279.5 / .S766 2013
519.542
Bayes' rule : a tutorial introduction to Bayesian analysis / James V Stone. - First Edition. - 170 pages : illustrations ; 23 cm
"A tutorial introduction book"--Page 4 of cover.
Includes bibliographical references and index.
An introduction to Bayes' rule -- Bayes' rule in pictures -- Discrete parameter values -- Continuous parameter values -- Gaussian parameter estimation -- A bird's eye view of Bayes' rule -- Bayesian wars -- Appendices. A. Glossary ; B. Mathematical symbols ; C. The rules of probability ; D. Probability density functions ; E. The binomial distribution ; F. The Gaussian distribution ; G. Least-squares estimation ; H. Reference priors ; I. MatLab code.
"Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. Bayes' rule is derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and online Python programs provided. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for the novice who wishes to become familiar with the basic principles of Bayesian analysis."--Publisher's description.
0956372848 9780956372840
Bayesian statistical decision theory.
QA279.5 / .S766 2013
519.542